时延法纯侧音测距体制针对星上应答机侧音反相的解决方法

针对中法测控合作中法方星上应答机出现的侧音反相问题,以某采用时延法纯侧音测距体制的测控系统为例,提出两种解决方法,并在自校、对塔标校和中法联网试验中进行验证.     

Robust ergodic rate transmission for time division duplex beamforming systems

In time division duplex(TDD)beamforming systems,the base station estimates the channel state information(CSI)at transmitter based on uplink pilots and then uses it to generate the beamforming vector in the downlink transmission.Because of the constraints of the TDD frame structure and the uplink pilot overhead,there inevitably exists CSI delay and channel estimation error between CSI estimation and downlink transmission channel,which would degrade system ergodic rate.In this paper,we propose a robust ergodic rate transmission scheme,in which the uplink pilot time interval(UPTI)of an active user is adaptively adjusted according to the changing channel conditions such as Doppler frequency shift,uplink pilot signal to noise ratio(SNR),to minimize the impact of CSI delay and channel estimation error on the ergodic rate of TDD beamforming systems.In order to get the optimal UPTI,we first derive the average post-processing SNR for TDD beamforming systems with channel estimation error and CSI delay.We then obtain the optimal UPTI,which maximizes the average post-processing SNR,given the normalized pilot overhead(the number of pilot symbols per data symbol).The numerical simulation results validate that the the proposed robust ergodic rate transmission scheme not only maximizes the average post-processing SNR but also maximizes the system ergodic rate.Moreover,the scheme can adapt well to the changing channel environments compared with the current fixed UPTI scheme.Especially our research is valuable for the uplink sounding reference signal design in long term evolution advanced(LTEAdvanced)system.     

Two States CBR Modeling of Data Source in Dynamic Traffic Monitoring Sensor Networks

Real traffic information was analyzed in the statistical characteristics and approximated as a Gaussian time series. A data source model, called two states constant bit rate (TSCBR), was proposed in dynamic traffic monitoring sensor networks. Analysis of autocorrelation of the models shows that the proposed TSCBR model matches with the statistical characteristics of real data source closely. To further verify the validity of the TSCBR data source model, the performance metrics of power consumption and network lifetime was studied in the evaluation of sensor media access control (SMAC) algorithm. The simulation results show that compared with traditional data source models, TSCBR model can significantly improve accuracy of the algorithm evaluation.     

Lattice reduction aided MMSE Tomlinson-Harashima precoding based on VBLAST algorithm for MIMO systems

A lattice reduction aided （LRA） minimum mean square error （MMSE） Tomlinson-Harashima precoding （THP） was proposed based on vertical Bell Labs layered space time （VBLAST） algorithm for multiple input multiple output （MIMO） systems. The extended channel was used to provide optimal tradeoff between residual interference and noise amplification. The processing based on lattice reduction method helps achieve maximal diversity order. The VBLAST algorithm was applied to get the optimal processing ordering for successive interference cancellation （SIC） at transmitter. Simulation results show that the proposed algorithm outperforms conventional THP and the LRA zero-forcing （ZF） THP with full diversity order.     

A novel vertical handoff algorithm based on fuzzy logic in aid of grey prediction theory in wireless heterogeneous networks

To coordinate the various access technologies in the 4G communication system, intelligent vertical handoff algorithms are required. This paper mainly deals with a novel vertical handoff decision algorithm based on fuzzy logic with the aid of grey theory and dynamic weights adaptation. The grey prediction theory (GPT) takes 4 sampled received signal strengths as input parameters, and calculates the predicted received signal strength in order to reduce the call dropping probability. The fuzzy logic theory based quantitative decision algorithm takes 3 quality of service (QoS) metric, received signal strength (RSS), available bandwidth (BW), and monetary cost (MC) of candidate networks as input parameters. The weight of each QoS metrics is adjusted along with the networks changing to trace the network condition. The final optimized vertical handoff decision is made by comparing the quantitative decision values of the candidate networks. Simulation results demonstrate that the proposed algorithm provides high performance in heterogeneous as well as homogeneous network environments.     

Lattice-basis reduction precoding based on successive interference cancellation design for multiuser MIMO downlink system

Two kinds of lattice-basis reduction precoding schemes based on successive interference cancellation are proposed. The successive interference cancellation (SIC) structure can be obtained by either orthogonal and a right triangular matrix (QR) decomposition, or the Vertical Bell Labs Layered Space Time (VBLAST) algorithm which provides optimal user ordering. Moreover, the extended channel approach is applied to the proposed SICbased schemes. Simulation results show that the proposed schemes can achieve comparable BER performance to vector precoding (VP).     

A Distributed Virtual Backbone Formation for Wireless Ad Hoc and Sensor Networks

The virtual backbone is an approach for solving routing problems in wireless ad hoc and sensor networks. A connected dominating set (CDS) was proposed as a virtual backbone to improve the performance of wireless networks. The quality of a virtual backbone is measured not only by approximation factor, which is the ratio of its size to that of minimum CDS, but also time complexity and message complexity. In this paper, a distributed algorithm is presented to construct a minimum CDS for ad hoc and sensor networks. By destroying triangular loops in the virtual backbone, the proposed algorithm can effectively construct a CDS with smaller size. Moreover, our algorithm, which is fully localized, has a constant approximation ratio, linear message and time complexity, and low implementation complexity. The simulation results and theoretical analysis show that our algorithm has better efficiency and performance than conventional approaches.